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June 14, 2016

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Your results are an artifact. As the data dictionary for the taxi data set states, the tip_amount field is populated for credit card transactions but cash tips are not included.

Really good work processing these files. I wonder if what you've found is the likelihood of a driver declaring a tip, rather than a tip being left? i.e. if a driver gets a card payment it's hard to hide a tip, but a cash tip can go straight into their pocket and doesn't need to be declared. Not knowing taxi management structures or USA tax schemes, I have no idea if this is something they'd want to do!

Thanks for your comments!

Michael: we do see 0.0005490915 * 289816908 = 159136 cash tips in the dataset. It is quite possible that many cash tips were not recorded in this dataset.

Mike: great observation about the declaration of cash tips. Unfortunately we don't have data to compute the likelihood of declaring a cash tip.

It's nice demonstartion of handeling large files, but do you really need that amount of data to fit a logistic regression model. Would be interesting to see if you took a fraction of the data and rebuild the model an see if the resultaten are different.

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